130,632 research outputs found
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Chimpanzees consider humans' psychological states when drawing statistical inferences
No full textThis work was supported by a research grant of the German Science Foundation DFG (grant # RA 2155/3-1) to Hannes Rakoczy and Josep Call. Further, we acknowledge support by the Leibniz Association through funding for the Leibniz Science Campus Primate Cognition.Great apes have been shown to be intuitive statisticians: they can use proportional information within a population to make intuitive probability judgments about randomly drawn samples [1, J.E., J.C., J.H., E.H., and H.R., unpublished data]. Humans, from early infancy onward, functionally integrate intuitive statistics with other cognitive domains to judge the randomness of an event [2; 3; 4; 5 ; 6]. To date, nothing is known about such cross-domain integration in any nonhuman animal, leaving uncertainty about the origins of human statistical abilities. We investigated whether chimpanzees take into account information about psychological states of experimenters (their biases and visual access) when drawing statistical inferences. We tested 21 sanctuary-living chimpanzees in a previously established paradigm that required subjects to infer which of two mixed populations of preferred and non-preferred food items was more likely to lead to a desired outcome for the subject. In a series of three experiments, we found that chimpanzees chose based on proportional information alone when they had no information about experimenters’ preferences and (to a lesser extent) when experimenters had biases for certain food types but drew blindly. By contrast, when biased experimenters had visual access, subjects ignored statistical information and instead chose based on experimenters’ biases. Lastly, chimpanzees intuitively used a violation of statistical likelihoods as indication for biased sampling. Our results suggest that chimpanzees have a random sampling assumption that can be overridden under the appropriate circumstances and that they are able to use mental state information to judge whether this is necessary. This provides further evidence for a shared statistical inference mechanism in apes and humans.Peer reviewe
Minds, persons, and space: An fMRI investigation into the relational complexity of higher-order intentionality
No full textMental state reasoning or theory-of-mind has been the subject of a rich body of imaging research. Although such investigations routinely tap a common set of regions, the precise function of each area remains a contentious matter. With the help of functional magnetic resonance imaging (fMRI), we sought to determine which areas are involved when processing mental state or intentional metarepresentations by focusing on the relational aspect of such representations. Using non-intentional relational representations such as spatial relations between persons and between objects as a contrast, the results ascertained the involvement of the precuneus, the temporal poles, and the medial prefrontal cortex in the processing of intentional representations. In contrast, the anterior superior temporal sulcus and the left temporo-parietal junction were implicated when processing representations that refer to the presence of persons in relational contexts in general. The right temporo-parietal junction, however, was specifically activated for persons entering spatial relations. The level of representational complexity, a previously unexplored factor, was also found to modulate the neural response in some brain regions, such as the medial prefrontal cortex and the right temporo-parietal junction. These findings highlight the need to take into account the critical roles played by an extensive network of neural regions during mental state reasoning
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
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